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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_harrell_davies.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationMon, 27 Oct 2008 14:38:38 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/27/t1225139955unw7b9thrf3jywd.htm/, Retrieved Sun, 19 May 2024 00:53:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19589, Retrieved Sun, 19 May 2024 00:53:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact166

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Harrell-Davis Quantiles] [Investigating dis...] [2007-10-22 20:06:26] [b9964c45117f7aac638ab9056d451faa]
-   PD  [Harrell-Davis Quantiles] [] [2008-10-26 16:09:06] [a4ee3bef49b119f4bd2e925060c84f5e]
F           [Harrell-Davis Quantiles] [q9 invest. distr.] [2008-10-27 20:38:38] [3762bf489501725951ad2579179cae2a] [Current]
Feedback Forum
2008-11-01 15:53:38 [Stéphanie Thijs] [reply] 
We zoeken een betrouwbaarheidsinterval voor de random component, niet voor de tijdreeks in zijn geheel. De random component bekom je door het gemiddelde van de tijdreeks af te trekken van de waarden van die tijdreeks. Op basis van deze 'nieuwe' tijdreeks, die bestaat uit de random components, bereken je het betrouwbaarheidsinterval.
2008-11-03 11:11:12 [Astrid Sniekers] [reply] 
Deze oefening had de student volgens mij anders moeten doen.

http://www.freestatistics.org/blog/date/2008/Nov/01/t1225540246hw8i858zoicz8ma.htm

De step size heb ik op 0,05 gezet. Ik heb in de tabel gekeken wanneer in de kolom ‘standard error’ de getallen grotere stappen vertoont. Dit zijn dan de extremen en deze moeten we eruit halen. Vanaf 0,04 beginnen de kleinere stapjes elkaar op te volgen tot en met 0,96, daarna krijgen we weer extremen. Dit kunt u ook zien in de grafiek.

Dit wil zeggen dat we een betrouwbaarheidsinterval hebben van 92%.

Verder had de student de oefening analoog aan vraag Q5 moeten oplossen.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
22780
17351
21382
24561
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ 72.249.76.132

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19589&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19589&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19589&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ 72.249.76.132






Harrell-Davis Quantiles
quantilesvaluestandard error
0.019809.038295303761238.52710785439
0.0210508.25104596471278.18809888874
0.0311299.40219552981478.73912996821
0.0412113.05652340961733.77656369238
0.0512932.07507561691940.31050716421
0.0613740.72800295102036.76400060663
0.0714511.65958156121998.73506747487
0.0815213.57276228011836.52234202212
0.0915821.70326232981587.36223821776
0.116324.01619385161300.93718890232
0.1116722.14609210861023.94162777105
0.1217028.4327102530789.490572090946
0.1317261.1450235063613.838260741387
0.1417439.8297047183498.034463416376
0.1517582.0005705792432.364734610838
0.1617701.5258424394402.427386661838
0.1717808.4282926541395.319414882617
0.1817909.5286315536402.904149486971
0.1918009.3782559308421.262168606774
0.218111.1024889758448.86215890111
0.2118216.9799327284484.703368611732
0.2218328.7415836997527.552351139668
0.2318447.6615806483575.288728264902
0.2418574.5390984428625.351980524641
0.2518709.659519221674.848927796991
0.2618852.7935238895721.149341942148
0.2719003.2600653762762.17708370619
0.2819160.0516962255796.646661601808
0.2919322.0019064383824.475848961888
0.319487.9645123576846.281928674363
0.3119656.9737678463863.754869318818
0.3219828.3591080718878.95779973626
0.3320001.7982881133894.056417289095
0.3420177.3049027340910.901672635379
0.3520355.1585089857930.704386769819
0.3620535.7955710948953.826906832735
0.3720719.6853965702979.706022209887
0.3820907.21609450231007.28439980296
0.3921098.61133103291034.99121977158
0.421293.89031441341061.35900289439
0.4121492.87293015341085.14310532576
0.4221695.22167187491105.66845556865
0.4321900.50432465001122.73814772119
0.4422108.25797527761136.67251477358
0.4522318.03649741361148.01907996897
0.4622529.42958967941157.30761265022
0.4722742.05004367711164.70049369163
0.4822955.49487458251170.09063486107
0.4923169.29296512631172.71860252085
0.523382.85529855141171.56542267276
0.5123595.44308208121165.49841841433
0.5223806.16461675931153.40238359665
0.5324014.00506008611134.53824353994
0.5424217.88606487351108.77901713588
0.5524416.74634454751076.43718635238
0.5624609.63066221891038.39102330008
0.5724795.7740091389996.125424897425
0.5824974.6696177426951.241668963896
0.5925146.1132949371905.741664601115
0.625310.2215086019861.446267816857
0.6125467.4258169328820.118178670242
0.6225618.4507048976783.318370843728
0.6325764.2847867915752.283235305042
0.6425906.1557697557728.035295387077
0.6526045.5168486105711.448502591248
0.6626184.0461115504703.400839878185
0.6726323.6517682047704.990431662811
0.6826466.4664498347717.376567138754
0.6926614.8065232712741.61422152258
0.726771.070966859778.298661730965
0.7126937.5620464849826.700560816713
0.7227116.2280157820884.558078885518
0.7327308.3542537796947.5166838478
0.7427514.25765130331009.56467540958
0.7527733.06053070581063.67213870687
0.7627962.62501994421102.84457046348
0.7728199.70946500161121.45101201671
0.7828440.36440719411116.451258616
0.7928680.52462230321088.31287089388
0.828916.69121015251041.17814460776
0.8129146.5530200751982.447655116102
0.8229369.3868054189921.42702040831
0.8329586.1091936914867.365336330586
0.8429798.9278680705827.001845348221
0.8530010.6397206563802.600253107863
0.8630223.727623784790.890294535691
0.8730439.4908029863784.100435076175
0.8830657.4905034945772.635383244726
0.8930875.6070879444748.048010624926
0.931091.0193881959705.994575544626
0.9131302.4700458254648.955595607182
0.9231514.2235184475589.630600622527
0.9331741.8650126114557.663625145333
0.9432018.9265289596608.312918561527
0.9532400.6660023217801.03221968084
0.9632957.27831814051136.21287046079
0.9733744.65745191051521.44635030259
0.9834740.84868959671801.35380291562
0.9935759.27253983461896.94245770970

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 9809.03829530376 & 1238.52710785439 \tabularnewline
0.02 & 10508.2510459647 & 1278.18809888874 \tabularnewline
0.03 & 11299.4021955298 & 1478.73912996821 \tabularnewline
0.04 & 12113.0565234096 & 1733.77656369238 \tabularnewline
0.05 & 12932.0750756169 & 1940.31050716421 \tabularnewline
0.06 & 13740.7280029510 & 2036.76400060663 \tabularnewline
0.07 & 14511.6595815612 & 1998.73506747487 \tabularnewline
0.08 & 15213.5727622801 & 1836.52234202212 \tabularnewline
0.09 & 15821.7032623298 & 1587.36223821776 \tabularnewline
0.1 & 16324.0161938516 & 1300.93718890232 \tabularnewline
0.11 & 16722.1460921086 & 1023.94162777105 \tabularnewline
0.12 & 17028.4327102530 & 789.490572090946 \tabularnewline
0.13 & 17261.1450235063 & 613.838260741387 \tabularnewline
0.14 & 17439.8297047183 & 498.034463416376 \tabularnewline
0.15 & 17582.0005705792 & 432.364734610838 \tabularnewline
0.16 & 17701.5258424394 & 402.427386661838 \tabularnewline
0.17 & 17808.4282926541 & 395.319414882617 \tabularnewline
0.18 & 17909.5286315536 & 402.904149486971 \tabularnewline
0.19 & 18009.3782559308 & 421.262168606774 \tabularnewline
0.2 & 18111.1024889758 & 448.86215890111 \tabularnewline
0.21 & 18216.9799327284 & 484.703368611732 \tabularnewline
0.22 & 18328.7415836997 & 527.552351139668 \tabularnewline
0.23 & 18447.6615806483 & 575.288728264902 \tabularnewline
0.24 & 18574.5390984428 & 625.351980524641 \tabularnewline
0.25 & 18709.659519221 & 674.848927796991 \tabularnewline
0.26 & 18852.7935238895 & 721.149341942148 \tabularnewline
0.27 & 19003.2600653762 & 762.17708370619 \tabularnewline
0.28 & 19160.0516962255 & 796.646661601808 \tabularnewline
0.29 & 19322.0019064383 & 824.475848961888 \tabularnewline
0.3 & 19487.9645123576 & 846.281928674363 \tabularnewline
0.31 & 19656.9737678463 & 863.754869318818 \tabularnewline
0.32 & 19828.3591080718 & 878.95779973626 \tabularnewline
0.33 & 20001.7982881133 & 894.056417289095 \tabularnewline
0.34 & 20177.3049027340 & 910.901672635379 \tabularnewline
0.35 & 20355.1585089857 & 930.704386769819 \tabularnewline
0.36 & 20535.7955710948 & 953.826906832735 \tabularnewline
0.37 & 20719.6853965702 & 979.706022209887 \tabularnewline
0.38 & 20907.2160945023 & 1007.28439980296 \tabularnewline
0.39 & 21098.6113310329 & 1034.99121977158 \tabularnewline
0.4 & 21293.8903144134 & 1061.35900289439 \tabularnewline
0.41 & 21492.8729301534 & 1085.14310532576 \tabularnewline
0.42 & 21695.2216718749 & 1105.66845556865 \tabularnewline
0.43 & 21900.5043246500 & 1122.73814772119 \tabularnewline
0.44 & 22108.2579752776 & 1136.67251477358 \tabularnewline
0.45 & 22318.0364974136 & 1148.01907996897 \tabularnewline
0.46 & 22529.4295896794 & 1157.30761265022 \tabularnewline
0.47 & 22742.0500436771 & 1164.70049369163 \tabularnewline
0.48 & 22955.4948745825 & 1170.09063486107 \tabularnewline
0.49 & 23169.2929651263 & 1172.71860252085 \tabularnewline
0.5 & 23382.8552985514 & 1171.56542267276 \tabularnewline
0.51 & 23595.4430820812 & 1165.49841841433 \tabularnewline
0.52 & 23806.1646167593 & 1153.40238359665 \tabularnewline
0.53 & 24014.0050600861 & 1134.53824353994 \tabularnewline
0.54 & 24217.8860648735 & 1108.77901713588 \tabularnewline
0.55 & 24416.7463445475 & 1076.43718635238 \tabularnewline
0.56 & 24609.6306622189 & 1038.39102330008 \tabularnewline
0.57 & 24795.7740091389 & 996.125424897425 \tabularnewline
0.58 & 24974.6696177426 & 951.241668963896 \tabularnewline
0.59 & 25146.1132949371 & 905.741664601115 \tabularnewline
0.6 & 25310.2215086019 & 861.446267816857 \tabularnewline
0.61 & 25467.4258169328 & 820.118178670242 \tabularnewline
0.62 & 25618.4507048976 & 783.318370843728 \tabularnewline
0.63 & 25764.2847867915 & 752.283235305042 \tabularnewline
0.64 & 25906.1557697557 & 728.035295387077 \tabularnewline
0.65 & 26045.5168486105 & 711.448502591248 \tabularnewline
0.66 & 26184.0461115504 & 703.400839878185 \tabularnewline
0.67 & 26323.6517682047 & 704.990431662811 \tabularnewline
0.68 & 26466.4664498347 & 717.376567138754 \tabularnewline
0.69 & 26614.8065232712 & 741.61422152258 \tabularnewline
0.7 & 26771.070966859 & 778.298661730965 \tabularnewline
0.71 & 26937.5620464849 & 826.700560816713 \tabularnewline
0.72 & 27116.2280157820 & 884.558078885518 \tabularnewline
0.73 & 27308.3542537796 & 947.5166838478 \tabularnewline
0.74 & 27514.2576513033 & 1009.56467540958 \tabularnewline
0.75 & 27733.0605307058 & 1063.67213870687 \tabularnewline
0.76 & 27962.6250199442 & 1102.84457046348 \tabularnewline
0.77 & 28199.7094650016 & 1121.45101201671 \tabularnewline
0.78 & 28440.3644071941 & 1116.451258616 \tabularnewline
0.79 & 28680.5246223032 & 1088.31287089388 \tabularnewline
0.8 & 28916.6912101525 & 1041.17814460776 \tabularnewline
0.81 & 29146.5530200751 & 982.447655116102 \tabularnewline
0.82 & 29369.3868054189 & 921.42702040831 \tabularnewline
0.83 & 29586.1091936914 & 867.365336330586 \tabularnewline
0.84 & 29798.9278680705 & 827.001845348221 \tabularnewline
0.85 & 30010.6397206563 & 802.600253107863 \tabularnewline
0.86 & 30223.727623784 & 790.890294535691 \tabularnewline
0.87 & 30439.4908029863 & 784.100435076175 \tabularnewline
0.88 & 30657.4905034945 & 772.635383244726 \tabularnewline
0.89 & 30875.6070879444 & 748.048010624926 \tabularnewline
0.9 & 31091.0193881959 & 705.994575544626 \tabularnewline
0.91 & 31302.4700458254 & 648.955595607182 \tabularnewline
0.92 & 31514.2235184475 & 589.630600622527 \tabularnewline
0.93 & 31741.8650126114 & 557.663625145333 \tabularnewline
0.94 & 32018.9265289596 & 608.312918561527 \tabularnewline
0.95 & 32400.6660023217 & 801.03221968084 \tabularnewline
0.96 & 32957.2783181405 & 1136.21287046079 \tabularnewline
0.97 & 33744.6574519105 & 1521.44635030259 \tabularnewline
0.98 & 34740.8486895967 & 1801.35380291562 \tabularnewline
0.99 & 35759.2725398346 & 1896.94245770970 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19589&T=1

[TABLE]
[ROW][C]Harrell-Davis Quantiles[/C][/ROW]
[ROW][C]quantiles[/C][C]value[/C][C]standard error[/C][/ROW]
[ROW][C]0.01[/C][C]9809.03829530376[/C][C]1238.52710785439[/C][/ROW]
[ROW][C]0.02[/C][C]10508.2510459647[/C][C]1278.18809888874[/C][/ROW]
[ROW][C]0.03[/C][C]11299.4021955298[/C][C]1478.73912996821[/C][/ROW]
[ROW][C]0.04[/C][C]12113.0565234096[/C][C]1733.77656369238[/C][/ROW]
[ROW][C]0.05[/C][C]12932.0750756169[/C][C]1940.31050716421[/C][/ROW]
[ROW][C]0.06[/C][C]13740.7280029510[/C][C]2036.76400060663[/C][/ROW]
[ROW][C]0.07[/C][C]14511.6595815612[/C][C]1998.73506747487[/C][/ROW]
[ROW][C]0.08[/C][C]15213.5727622801[/C][C]1836.52234202212[/C][/ROW]
[ROW][C]0.09[/C][C]15821.7032623298[/C][C]1587.36223821776[/C][/ROW]
[ROW][C]0.1[/C][C]16324.0161938516[/C][C]1300.93718890232[/C][/ROW]
[ROW][C]0.11[/C][C]16722.1460921086[/C][C]1023.94162777105[/C][/ROW]
[ROW][C]0.12[/C][C]17028.4327102530[/C][C]789.490572090946[/C][/ROW]
[ROW][C]0.13[/C][C]17261.1450235063[/C][C]613.838260741387[/C][/ROW]
[ROW][C]0.14[/C][C]17439.8297047183[/C][C]498.034463416376[/C][/ROW]
[ROW][C]0.15[/C][C]17582.0005705792[/C][C]432.364734610838[/C][/ROW]
[ROW][C]0.16[/C][C]17701.5258424394[/C][C]402.427386661838[/C][/ROW]
[ROW][C]0.17[/C][C]17808.4282926541[/C][C]395.319414882617[/C][/ROW]
[ROW][C]0.18[/C][C]17909.5286315536[/C][C]402.904149486971[/C][/ROW]
[ROW][C]0.19[/C][C]18009.3782559308[/C][C]421.262168606774[/C][/ROW]
[ROW][C]0.2[/C][C]18111.1024889758[/C][C]448.86215890111[/C][/ROW]
[ROW][C]0.21[/C][C]18216.9799327284[/C][C]484.703368611732[/C][/ROW]
[ROW][C]0.22[/C][C]18328.7415836997[/C][C]527.552351139668[/C][/ROW]
[ROW][C]0.23[/C][C]18447.6615806483[/C][C]575.288728264902[/C][/ROW]
[ROW][C]0.24[/C][C]18574.5390984428[/C][C]625.351980524641[/C][/ROW]
[ROW][C]0.25[/C][C]18709.659519221[/C][C]674.848927796991[/C][/ROW]
[ROW][C]0.26[/C][C]18852.7935238895[/C][C]721.149341942148[/C][/ROW]
[ROW][C]0.27[/C][C]19003.2600653762[/C][C]762.17708370619[/C][/ROW]
[ROW][C]0.28[/C][C]19160.0516962255[/C][C]796.646661601808[/C][/ROW]
[ROW][C]0.29[/C][C]19322.0019064383[/C][C]824.475848961888[/C][/ROW]
[ROW][C]0.3[/C][C]19487.9645123576[/C][C]846.281928674363[/C][/ROW]
[ROW][C]0.31[/C][C]19656.9737678463[/C][C]863.754869318818[/C][/ROW]
[ROW][C]0.32[/C][C]19828.3591080718[/C][C]878.95779973626[/C][/ROW]
[ROW][C]0.33[/C][C]20001.7982881133[/C][C]894.056417289095[/C][/ROW]
[ROW][C]0.34[/C][C]20177.3049027340[/C][C]910.901672635379[/C][/ROW]
[ROW][C]0.35[/C][C]20355.1585089857[/C][C]930.704386769819[/C][/ROW]
[ROW][C]0.36[/C][C]20535.7955710948[/C][C]953.826906832735[/C][/ROW]
[ROW][C]0.37[/C][C]20719.6853965702[/C][C]979.706022209887[/C][/ROW]
[ROW][C]0.38[/C][C]20907.2160945023[/C][C]1007.28439980296[/C][/ROW]
[ROW][C]0.39[/C][C]21098.6113310329[/C][C]1034.99121977158[/C][/ROW]
[ROW][C]0.4[/C][C]21293.8903144134[/C][C]1061.35900289439[/C][/ROW]
[ROW][C]0.41[/C][C]21492.8729301534[/C][C]1085.14310532576[/C][/ROW]
[ROW][C]0.42[/C][C]21695.2216718749[/C][C]1105.66845556865[/C][/ROW]
[ROW][C]0.43[/C][C]21900.5043246500[/C][C]1122.73814772119[/C][/ROW]
[ROW][C]0.44[/C][C]22108.2579752776[/C][C]1136.67251477358[/C][/ROW]
[ROW][C]0.45[/C][C]22318.0364974136[/C][C]1148.01907996897[/C][/ROW]
[ROW][C]0.46[/C][C]22529.4295896794[/C][C]1157.30761265022[/C][/ROW]
[ROW][C]0.47[/C][C]22742.0500436771[/C][C]1164.70049369163[/C][/ROW]
[ROW][C]0.48[/C][C]22955.4948745825[/C][C]1170.09063486107[/C][/ROW]
[ROW][C]0.49[/C][C]23169.2929651263[/C][C]1172.71860252085[/C][/ROW]
[ROW][C]0.5[/C][C]23382.8552985514[/C][C]1171.56542267276[/C][/ROW]
[ROW][C]0.51[/C][C]23595.4430820812[/C][C]1165.49841841433[/C][/ROW]
[ROW][C]0.52[/C][C]23806.1646167593[/C][C]1153.40238359665[/C][/ROW]
[ROW][C]0.53[/C][C]24014.0050600861[/C][C]1134.53824353994[/C][/ROW]
[ROW][C]0.54[/C][C]24217.8860648735[/C][C]1108.77901713588[/C][/ROW]
[ROW][C]0.55[/C][C]24416.7463445475[/C][C]1076.43718635238[/C][/ROW]
[ROW][C]0.56[/C][C]24609.6306622189[/C][C]1038.39102330008[/C][/ROW]
[ROW][C]0.57[/C][C]24795.7740091389[/C][C]996.125424897425[/C][/ROW]
[ROW][C]0.58[/C][C]24974.6696177426[/C][C]951.241668963896[/C][/ROW]
[ROW][C]0.59[/C][C]25146.1132949371[/C][C]905.741664601115[/C][/ROW]
[ROW][C]0.6[/C][C]25310.2215086019[/C][C]861.446267816857[/C][/ROW]
[ROW][C]0.61[/C][C]25467.4258169328[/C][C]820.118178670242[/C][/ROW]
[ROW][C]0.62[/C][C]25618.4507048976[/C][C]783.318370843728[/C][/ROW]
[ROW][C]0.63[/C][C]25764.2847867915[/C][C]752.283235305042[/C][/ROW]
[ROW][C]0.64[/C][C]25906.1557697557[/C][C]728.035295387077[/C][/ROW]
[ROW][C]0.65[/C][C]26045.5168486105[/C][C]711.448502591248[/C][/ROW]
[ROW][C]0.66[/C][C]26184.0461115504[/C][C]703.400839878185[/C][/ROW]
[ROW][C]0.67[/C][C]26323.6517682047[/C][C]704.990431662811[/C][/ROW]
[ROW][C]0.68[/C][C]26466.4664498347[/C][C]717.376567138754[/C][/ROW]
[ROW][C]0.69[/C][C]26614.8065232712[/C][C]741.61422152258[/C][/ROW]
[ROW][C]0.7[/C][C]26771.070966859[/C][C]778.298661730965[/C][/ROW]
[ROW][C]0.71[/C][C]26937.5620464849[/C][C]826.700560816713[/C][/ROW]
[ROW][C]0.72[/C][C]27116.2280157820[/C][C]884.558078885518[/C][/ROW]
[ROW][C]0.73[/C][C]27308.3542537796[/C][C]947.5166838478[/C][/ROW]
[ROW][C]0.74[/C][C]27514.2576513033[/C][C]1009.56467540958[/C][/ROW]
[ROW][C]0.75[/C][C]27733.0605307058[/C][C]1063.67213870687[/C][/ROW]
[ROW][C]0.76[/C][C]27962.6250199442[/C][C]1102.84457046348[/C][/ROW]
[ROW][C]0.77[/C][C]28199.7094650016[/C][C]1121.45101201671[/C][/ROW]
[ROW][C]0.78[/C][C]28440.3644071941[/C][C]1116.451258616[/C][/ROW]
[ROW][C]0.79[/C][C]28680.5246223032[/C][C]1088.31287089388[/C][/ROW]
[ROW][C]0.8[/C][C]28916.6912101525[/C][C]1041.17814460776[/C][/ROW]
[ROW][C]0.81[/C][C]29146.5530200751[/C][C]982.447655116102[/C][/ROW]
[ROW][C]0.82[/C][C]29369.3868054189[/C][C]921.42702040831[/C][/ROW]
[ROW][C]0.83[/C][C]29586.1091936914[/C][C]867.365336330586[/C][/ROW]
[ROW][C]0.84[/C][C]29798.9278680705[/C][C]827.001845348221[/C][/ROW]
[ROW][C]0.85[/C][C]30010.6397206563[/C][C]802.600253107863[/C][/ROW]
[ROW][C]0.86[/C][C]30223.727623784[/C][C]790.890294535691[/C][/ROW]
[ROW][C]0.87[/C][C]30439.4908029863[/C][C]784.100435076175[/C][/ROW]
[ROW][C]0.88[/C][C]30657.4905034945[/C][C]772.635383244726[/C][/ROW]
[ROW][C]0.89[/C][C]30875.6070879444[/C][C]748.048010624926[/C][/ROW]
[ROW][C]0.9[/C][C]31091.0193881959[/C][C]705.994575544626[/C][/ROW]
[ROW][C]0.91[/C][C]31302.4700458254[/C][C]648.955595607182[/C][/ROW]
[ROW][C]0.92[/C][C]31514.2235184475[/C][C]589.630600622527[/C][/ROW]
[ROW][C]0.93[/C][C]31741.8650126114[/C][C]557.663625145333[/C][/ROW]
[ROW][C]0.94[/C][C]32018.9265289596[/C][C]608.312918561527[/C][/ROW]
[ROW][C]0.95[/C][C]32400.6660023217[/C][C]801.03221968084[/C][/ROW]
[ROW][C]0.96[/C][C]32957.2783181405[/C][C]1136.21287046079[/C][/ROW]
[ROW][C]0.97[/C][C]33744.6574519105[/C][C]1521.44635030259[/C][/ROW]
[ROW][C]0.98[/C][C]34740.8486895967[/C][C]1801.35380291562[/C][/ROW]
[ROW][C]0.99[/C][C]35759.2725398346[/C][C]1896.94245770970[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19589&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19589&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Harrell-Davis Quantiles
quantilesvaluestandard error
0.019809.038295303761238.52710785439
0.0210508.25104596471278.18809888874
0.0311299.40219552981478.73912996821
0.0412113.05652340961733.77656369238
0.0512932.07507561691940.31050716421
0.0613740.72800295102036.76400060663
0.0714511.65958156121998.73506747487
0.0815213.57276228011836.52234202212
0.0915821.70326232981587.36223821776
0.116324.01619385161300.93718890232
0.1116722.14609210861023.94162777105
0.1217028.4327102530789.490572090946
0.1317261.1450235063613.838260741387
0.1417439.8297047183498.034463416376
0.1517582.0005705792432.364734610838
0.1617701.5258424394402.427386661838
0.1717808.4282926541395.319414882617
0.1817909.5286315536402.904149486971
0.1918009.3782559308421.262168606774
0.218111.1024889758448.86215890111
0.2118216.9799327284484.703368611732
0.2218328.7415836997527.552351139668
0.2318447.6615806483575.288728264902
0.2418574.5390984428625.351980524641
0.2518709.659519221674.848927796991
0.2618852.7935238895721.149341942148
0.2719003.2600653762762.17708370619
0.2819160.0516962255796.646661601808
0.2919322.0019064383824.475848961888
0.319487.9645123576846.281928674363
0.3119656.9737678463863.754869318818
0.3219828.3591080718878.95779973626
0.3320001.7982881133894.056417289095
0.3420177.3049027340910.901672635379
0.3520355.1585089857930.704386769819
0.3620535.7955710948953.826906832735
0.3720719.6853965702979.706022209887
0.3820907.21609450231007.28439980296
0.3921098.61133103291034.99121977158
0.421293.89031441341061.35900289439
0.4121492.87293015341085.14310532576
0.4221695.22167187491105.66845556865
0.4321900.50432465001122.73814772119
0.4422108.25797527761136.67251477358
0.4522318.03649741361148.01907996897
0.4622529.42958967941157.30761265022
0.4722742.05004367711164.70049369163
0.4822955.49487458251170.09063486107
0.4923169.29296512631172.71860252085
0.523382.85529855141171.56542267276
0.5123595.44308208121165.49841841433
0.5223806.16461675931153.40238359665
0.5324014.00506008611134.53824353994
0.5424217.88606487351108.77901713588
0.5524416.74634454751076.43718635238
0.5624609.63066221891038.39102330008
0.5724795.7740091389996.125424897425
0.5824974.6696177426951.241668963896
0.5925146.1132949371905.741664601115
0.625310.2215086019861.446267816857
0.6125467.4258169328820.118178670242
0.6225618.4507048976783.318370843728
0.6325764.2847867915752.283235305042
0.6425906.1557697557728.035295387077
0.6526045.5168486105711.448502591248
0.6626184.0461115504703.400839878185
0.6726323.6517682047704.990431662811
0.6826466.4664498347717.376567138754
0.6926614.8065232712741.61422152258
0.726771.070966859778.298661730965
0.7126937.5620464849826.700560816713
0.7227116.2280157820884.558078885518
0.7327308.3542537796947.5166838478
0.7427514.25765130331009.56467540958
0.7527733.06053070581063.67213870687
0.7627962.62501994421102.84457046348
0.7728199.70946500161121.45101201671
0.7828440.36440719411116.451258616
0.7928680.52462230321088.31287089388
0.828916.69121015251041.17814460776
0.8129146.5530200751982.447655116102
0.8229369.3868054189921.42702040831
0.8329586.1091936914867.365336330586
0.8429798.9278680705827.001845348221
0.8530010.6397206563802.600253107863
0.8630223.727623784790.890294535691
0.8730439.4908029863784.100435076175
0.8830657.4905034945772.635383244726
0.8930875.6070879444748.048010624926
0.931091.0193881959705.994575544626
0.9131302.4700458254648.955595607182
0.9231514.2235184475589.630600622527
0.9331741.8650126114557.663625145333
0.9432018.9265289596608.312918561527
0.9532400.6660023217801.03221968084
0.9632957.27831814051136.21287046079
0.9733744.65745191051521.44635030259
0.9834740.84868959671801.35380291562
0.9935759.27253983461896.94245770970


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
Parameters (R input):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
R code (references can be found in the software module):
par1 <- as(par1,'numeric')
par2 <- as(par2,'numeric')
par3 <- as(par3,'numeric')
library(Hmisc)
myseq <- seq(par1, par2, par3)
hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE)
bitmap(file='test1.png')
plot(myseq,hd,col=2,main=main,xlab=xlab,ylab=ylab)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Harrell-Davis Quantiles',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'quantiles',header=TRUE)
a<-table.element(a,'value',header=TRUE)
a<-table.element(a,'standard error',header=TRUE)
a<-table.row.end(a)
length(hd)
for (i in 1:length(hd))
{
a<-table.row.start(a)
a<-table.element(a,as(labels(hd)[i],'numeric'),header=TRUE)
a<-table.element(a,as.matrix(hd[i])[1,1])
a<-table.element(a,as.matrix(attr(hd,'se')[i])[1,1])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')